In order to capture an image having a higher quality, there has been proposed a dual-camera configuration. In such configuration, user equipment such as a mobile phone may be equipped with two cameras at one side. For example, a camera may be a black-white camera, while the other camera is a color camera. It has been found that under the same lighting condition, the exposure volume of the black-white camera is significantly larger than the color camera. As such, under a low-light condition, the black-white camera can still reach an appropriate exposure volume. By fusing an image captured by the black-white camera with an image captured by a color camera, the quality of a final image will be apparently superior to the image captured by using a single camera.
Although the dual-camera configuration is initially proposed for image capture in a low-light condition, such configuration may likewise be used for other imaging conditions. For different imaging conditions, when fusing the images captured by different cameras, it is needed to perform different processing and/or adopt different processing parameters. For example, under a normal light condition, a super resolution processing may be applied in fusing so as to enhance the resolution of an image. However, under a low-light condition, because there is a relatively large gap between the brightness of the images captured by two cameras, the super resolution processing cannot be performed. In other words, when capturing an image using a dual-camera configuration, a better post-processing can be performed by determining an imaging condition.
In practice, it is impractical to require a user to set an imaging condition in a manual manner. First, it will significantly increase user burden and dampen user experience. Moreover, for non-professional users, they can hardly set an imaging condition. Some traditional solutions detect an imaging condition through reading camera hardware parameters. For example, lighting in an environment may be detected based on scene reflectivity. However, such lighting detection is extremely sensitive to noise, thereby causing a detecting result instable. Moreover, not all cameras are equipped with hardware deeded for lighting detection. Besides, in addition to lighting, the imaging process is also affected by many other factors, such as the characteristics of an imaging sensor, and the like. Therefore, a method of simply reading hardware photosensitive parameters is unreliable for s dual-camera configuration.